Clinical Decision Support
As part of a Small Business Innovative Research(SBIR) grant awarded by National Institute on Drug Abuse(NIDA), FEi, partnering with Inflexxion (http://www.inflexxion.com/) is developing a Clinical Decision Support algorithm to advise clinicians to optimize a client’s chances of achieving improved outcomes following treatment.
Clinical Decision Support analyzes many factors, including:
- Client Demographics: race, ethnicity, age, and primary substance
- ASI-MV baseline outcome domains: employment, medical/health, housing, substance abuse, legal & justice status, /psychosocial, and length of stay in treatment
- ASI-MV follow-up outcomes domains: employment, medical/health, housing, substance abuse, legal & justice status, /psychosocial, and length of stay in treatment
- Treatment Service delivery: encounters, progress notes, duration, level of care, delivery setting, and cost
Follow-up assessments are planned on a fixed timeframe in order to calculate rates of change across outcomes domains.
The intention is to discover which treatment services, or pattern of services, are most closely correlated with positive outcomes change. Secondary analysis will attempt to identify any significant differences between client group characteristics such as primary substance, age and ethnicity.